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Computational intelligence (CI) lies at the interface between engineering and computer science; control engineering, where problems are solved using computer-assisted methods. Thus, it can be regarded as an indispensable basis for all artificial intelligence (AI) activities. This book collects surveys of most recent theoretical approaches focusing on fuzzy systems, neurocomputing, and nature inspired algorithms. It also presents surveys of up-to-date research and application with special focus on fuzzy systems as well as on applications in life sciences and neuronal computing.

Engineering sciences. Technology --- Computational intelligence.

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web intelligence --- system modelling --- data mining --- machine learning --- mathematical foundations of computational intelligence --- Computational intelligence --- Computational intelligence. --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Computer. Automation --- Computer Science

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"Fully revised and updated, this comprehensive new edition covers modern AI and machine learning for undergraduate and graduate students. Includes new chapters on deep learning including generative AI, causality and social impact, new social impact sections, major revisions to knowledge graphs, reasoning and decision-making, and more AIPython code"--

Computational intelligence --- Artificial intelligence --- General ethics --- Probability theory --- Computer science --- Artificial intelligence. Robotics. Simulation. Graphics

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This book presents thoughts and pathways to build revolutionary machine learning models with the new paradigm of machine learning to adapt behaviorism. It focuses on two aspects – one focuses on architecting a choice process to lead users on the certain choice path while the second focuses on developing machine learning models based on choice paradigm. This book is divided in three parts where part one deals with human choice and choice architecting models with stories of choice architects. Second part closely studies human choosing models and deliberates on developing machine learning models based on the human choice paradigm. Third part takes you further to look at machine learning based choice architecture. The proposed pioneering choice-based paradigm for machine learning presented in the book will help readers to develop products – help readers to solve problems in a more humanish way and to negotiate with uncertainty in a more graceful but in an objective way. It will help to create unprecedented value for business and society. Further, it will unveil a new paradigm for modern intelligent businesses to embark on the new journey; the journey of transition from shackled feature rich and choice poor systems to feature flexible and choice rich natural behaviors.

Computer science --- Programming --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- neuronale netwerken --- fuzzy logic --- cybernetica --- informatica --- programmeren (informatica) --- wiskunde --- KI (kunstmatige intelligentie) --- Computational intelligence. --- Machine learning. --- Computational Intelligence. --- Machine Learning. --- Mathematics of Computing. --- Mathematics. --- Consumer behavior --- AI (artificiële intelligentie)

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Preface In the axioms of probability theory proposed by Kolmogorov the basic "probabilistic" object is the concept of a probability model or probability space. This is a triple (n, F, P), where n is the space of elementary events or outcomes, F is a a-algebra of subsets of n announced by the events and P is a probability measure or a probability on the measure space (n, F). This generally accepted system of axioms of probability theory proved to be so successful that, apart from its simplicity, it enabled one to embrace the classical branches of probability theory and, at the same time, it paved the way for the development of new chapters in it, in particular, the theory of random (or stochastic) processes. In the theory of random processes, various classes of processes have been studied in depth. Theories of processes with independent increments, Markov processes, stationary processes, among others, have been constructed. In the formation and development of the theory of random processes, a significant event was the realization that the construction of a "general theory of ran­ dom processes" requires the introduction of a flow of a-algebras (a filtration) F = (Ftk::o supplementing the triple (n, F, P), where F is interpreted as t the collection of events from F observable up to time t.

Stochastic processes --- Processus stochastiques --- Stochastic processes. --- Probabilities. --- Statistics . --- Computational intelligence. --- Finance. --- Probability Theory and Stochastic Processes. --- Statistics, general. --- Computational Intelligence. --- Finance, general. --- Funding --- Funds --- Economics --- Currency question --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Mathematical statistics --- Risk